- Location
- Beijing, CN
- Type
- Full-time
- Department
- IT
- Closing date
- Today
- Source
- iCIMS
Description
Job Purpose
About the Role
We're looking for a mid-level technical specialist to join a team that supports AI data collection and annotation projects. The role sits at the intersection of engineering, automation, and analytics — the person will help production teams build and improve UI within our internal annotation and data collection tooling, design and optimize workflows, create reports and dashboards, and develop solutions to operational challenges.
About Train AI Data Services
Training or fine-tuning artificial intelligence (AI) requires data. LOTS of data. However, not just any data will do – our clients need responsible AI data that’s targeted, accurate and reliable to ensure machine learning (ML) success. But preparing AI training data is a monumental task that can take up the vast majority of AI project time, leaving AI teams with precious little time to focus on developing, deploying and evaluating ML models. TrainAI by RWS helps our clients address this challenge head-on.
With a seamless blend of technological understanding and human intelligence, TrainAI provides complete, end-to-end data collection and content generation, data annotation or labelling, human-in-the-loop data validation and generative AI data services for all types of AI, in any language, at any scale, based on the principles of responsible AI. Today, TrainAI supports four of the world’s top five technology companies, enhancing the performance of their generative AI applications by providing services such as prompt engineering, response refinement and red teaming with locale-specific domain experts across a broad range of topic areas and educational levels. Visit rws.com/trainai to learn more.
Job Overview
Key Responsibilities
Build, update, and improve UI components for internal annotation and data collection tools used by AI production teams.
Design, optimize, and standardize end-to-end production workflows to improve operational efficiency.
Develop, maintain, and update analytical reports and interactive dashboards using Power BI.
Write Python scripts to support data processing, pipeline automation, and internal tooling improvements.
Deploy and manage tooling updates using Azure cloud infrastructure and Azure DevOps, including CI/CD workflows.
Partner closely with cross-functional production teams to identify operational pain points and deliver practical, scalable solutions.
Interpret high-level, ambiguous business requests and convert them into structured technical deliverables without fully detailed specifications.
Continuously iterate on existing tools and processes to enhance stability, usability, and team productivity.
Skills & Experience
Hands-on experience building or improving internal tooling, UI interfaces, or operational workflows.
Basic to intermediate Python scripting and data processing capabilities.
Familiarity with Azure cloud environments and Azure DevOps (CI/CD and deployment).
Experience creating business reports and dashboards (Power BI preferred).
Basic understanding of AI, LLMs, prompt engineering, or AI training data workflows.
Exposure to AI-assisted coding tools (Cursor preferred).
Previous experience in data annotation, data collection pipelines, or AI training data operations is a strong plus.
Excellent cross-functional communication skills; able to bridge technical and non-technical stakeholders.
